Sam Altman made the correct diagnosis. The solution, however, will not come from politics, but from corporate management.

Last week, Sam Altman published a thirteen-page strategy paper entitled “Industrial Policy for the Intelligence Age: Ideas to Keep People First.” The message is as simple as it is consequential: AI is shifting the distribution of value from labor to capital. And if no one intervenes, the foundations of modern economies will crumble.

Altman calls for robot taxes, a government wealth fund, and a fundamental shift in the tax base: away from labor income and toward capital gains. This sounds like a New Deal 2.0—and that’s precisely the intention. The reference to the Progressive Era and the 1930s is no rhetorical accident.

Altman has clearly identified the macroeconomic problem. However, he’s addressing it from the wrong perspective. The decision that will actually shift the relationship between labor and capital isn’t made in politics. It’s made every day in the corporate world.

The core of his argument is macroeconomically precise: AI dramatically increases capital productivity. At the same time, the share of value creation that goes to workers as wages decreases. This is no longer a prediction—it is a measurable shift.

What Altman describes is the classic mechanism of factor substitution: When capital—in this case, AI—becomes cheaper, companies replace labor with capital. This increases profit margins. But at the same time, across all companies, it reduces the share of labor in the economy.

The effect itself is not new. It is as old as industrialization. What is new is its speed and scope. AI makes substitution possible in knowledge work—precisely where qualifications have long been considered a safeguard against automation.

The macroeconomic problem has its own logic—one that remains invisible at the company level. Every single company acts rationally: cutting costs, increasing margins, ensuring competitiveness. That’s efficiency. The problem arises when everyone does the same thing at once.

If labor income falls, purchasing power falls. If purchasing power falls, demand weakens. If demand weakens, even higher margins are no longer enough. This isn’t theory—it’s the classic Keynesian demand trap, this time triggered by technological upheaval rather than a financial crisis.

Altman’s answer: redistribution through taxes. A government wealth fund, financed by AI companies, gives every citizen a share of productivity growth. Demand remains stable, even if the share of labor decreases.

Economically sound. Politically? Not this decade. The Biden administration already failed to tax unrealized capital gains. The current administration has other priorities. And Europe—the most regulation-friendly territory—is fighting for competitiveness, not redistribution.

Because the political path is blocked, the real decision is made where it always has been: in companies. And there, the choice isn’t black and white—but the direction is.

Path 1 is the default. It’s easier to justify (cost savings are measurable), faster to implement, and simpler to explain in investor reports. It’s also the path that, on a large scale, leads to the trap Altman describes.

Path 2 requires a different starting point. Not: What can we automate? But rather: What can we do with AI that wasn’t possible before?

Many companies believe they are increasing their productivity. In reality, they are shrinking under controlled conditions. The difference is crucial—and invisible in most management dashboards.

Traditional efficiency metrics measure output per employee. If the number of employees decreases while output remains the same, the metric improves. This looks like increased productivity. In reality, it’s simply a smaller system producing the same amount as before.

True productivity growth means the system produces more—not that fewer people produce the same amount. The distinction may sound technical, but the strategic implications are fundamental.

Altman’s paper suggests that companies should leverage the efficiency gains of AI to retain employees, provide them with further training, and invest in a four-day workweek without any reduction in pay. For a tech CEO, this is an unusually conservative argument. And not an altruistic one: it’s about not eroding the demand base on which his own products depend.

At the company level, this translates into three concrete leadership decisions:

1. Every automation decision needs a growth hypothesis. Anyone automating a process should have a clear answer to: what do the freed-up capacities do instead? If the answer is “nothing,” it is cost reduction — not productivity growth.

2. Upskilling is not an HR initiative — it is capital allocation. Employees who can work with AI tools are more productive than employees who are replaced by AI tools. The ROI of Path 2 is harder to measure, but structurally more durable.

3. The next generation of management systems will not be built around cutting costs — but around making the right decisions and executing them. Which opportunities can we now seize that were previously out of reach? Which customer problems can we finally solve? These are the questions that make AI a strategic instrument rather than a cost lever. Companies that answer them well are not just protecting their margins. They are protecting the market they sell into.

Sam Altman describes a real problem with real urgency. His paper is not a PR exercise—it is a serious attempt to initiate a debate that policymakers have so far failed to address honestly.

But the solution he proposes requires governments to act quickly and coherently. That is—especially in the political climate he himself helps to shape—a bold assumption.

The real shift between labor and capital doesn’t happen through legislation. It happens through thousands of individual decisions within companies—every day, in every budget meeting, in every automation project.

That’s not bad news. It means: That’s where the solution lies.

Quellen: OpenAI, „Industrial Policy for the Intelligence Age: Ideas to Keep People First“ (April 2026) · Axios, Behind the Curtain: Sam’s Superintelligence New Deal (April 2026) · Fortune (April 2026) · IMF World Economic Outlook 2017 · OECD Compendium of Productivity Indicators 2025 · Karabarbounis & Neiman, The Global Decline of the Labour Share, QJE 2014